Face image matching using fractal dimension

A new method is presented in this paper for calculating the correspondence between two face images on a pixel by pixel basis. The concept of fractal dimension is used to develop the proposed non-parametric area-based image matching method which achieves a higher proportion of matched pixels for face images than some well-known methods.

[1]  Bidyut Baran Chaudhuri,et al.  An efficient approach to estimate fractal dimension of textural images , 1992, Pattern Recognit..

[2]  Edward H. Adelson,et al.  The extraction of Spatio-temporal Energy in Human and Machine Vision , 1997 .

[3]  David Beymer,et al.  Face recognition from one example view , 1995, Proceedings of IEEE International Conference on Computer Vision.

[4]  Jean Paul Rigaut,et al.  Automated image segmentation by mathematical morphology and fractal geometry , 1988 .

[5]  Shree K. Nayar,et al.  Ordinal measures for visual correspondence , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[6]  Alex Pentland,et al.  Shading into Texture , 1984, Artif. Intell..

[7]  Steven S. Beauchemin,et al.  The computation of optical flow , 1995, CSUR.

[8]  Peter I. Corke,et al.  Fast and Robust Stereo Matching Algorithms for Mining Automation , 1999, Digit. Signal Process..

[9]  Ramin Zabih,et al.  Non-parametric Local Transforms for Computing Visual Correspondence , 1994, ECCV.

[10]  James M. Keller,et al.  Texture description and segmentation through fractal geometry , 1989, Comput. Vis. Graph. Image Process..

[11]  Joseph Naor,et al.  Multiple Resolution Texture Analysis and Classification , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.